Analyzing user paths has always been a challenge in Google Analytics 360. Even with the classic session-pageview data model you’d have to be inventive to be able to see how users navigated through your site, where they were most likely to go after visiting a set of pages or taking an action. If you’ve ever thought about this you’ve probably ended up exporting GA data to BigQuery and writing some custom SQL to analyze navigation paths.

This is where the new app + web functionality steps in. The new cross-platform measurement tool is expecting to make the pathing less painful in Analytics. In addition to this, it’s also going to aggregate data from both environments in a single analysis canvas.

Path Analysis is a completely new feature within the Analysis section of the Analytics reporting UI. Therefore, you don’t have to export the data out of Analytics, create BigQuery infrastructure, and write complex queries to drive immediate insights.

It outperforms the existing Flow Visualization and Navigation Summary reports in Analytics and makes the pathing flexible and intuitive, with drag-and-drop ease. There is one difference, though: it’s only available in the new property type (app + web) and thus, is based on a different data model.

See It in Action

Let’s see in detail what Path Analysis has to offer. Once you create an app + web property and connect one or several data streams to it, after a period of collecting data, you’ll be able to create a new Path Analysis from the left-hand navigation pane.

Using this technique will allow you to:

Explore how users navigate in your site or app, what steps they frequently take and whether they’re always going to the pages/screens you expect them to;

See what actions and sequences of actions they perform once landed on the site/app or started a conversion funnel. Are these the actions you expect them to take?

Find out if there are stages where visitors experience troubles preventing them from completing your business goals. Do they go back at some point and go through a step once again?

Look into what users do after an app exception or seeing an error page on a site;

Analyze how a specific event impacts further users’ actions and whether this may discover some UX optimization insights.

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Anton Dolgiy

anton.dolgiy@delvepartners.com

Pathing Analysis in Google Analytics 360

Analyzing user paths has always been a challenge in Google Analytics 360. Even with the…

Pathing Analysis in Google Analytics 360

Analyzing user paths has always been a challenge in Google Analytics 360. Even with the classic session-pageview data model you’d have to be inventive to be able to see how users navigated through your site, where they were most likely to go after visiting a set of pages or taking an action. If you’ve ever thought about this you’ve probably ended up exporting GA data to BigQuery and writing some custom SQL to analyze navigation paths.

This is where the new app + web functionality steps in. The new cross-platform measurement tool is expecting to make the pathing less painful in Analytics. In addition to this, it’s also going to aggregate data from both environments in a single analysis canvas.

Path Analysis is a completely new feature within the Analysis section of the Analytics reporting UI. Therefore, you don’t have to export the data out of Analytics, create BigQuery infrastructure, and write complex queries to drive immediate insights.

It outperforms the existing Flow Visualization and Navigation Summary reports in Analytics and makes the pathing flexible and intuitive, with drag-and-drop ease. There is one difference, though: it’s only available in the new property type (app + web) and thus, is based on a different data model.

See It in Action

Let’s see in detail what Path Analysis has to offer. Once you create an app + web property and connect one or several data streams to it, after a period of collecting data, you’ll be able to create a new Path Analysis from the left-hand navigation pane.

Using this technique will allow you to:

Explore how users navigate in your site or app, what steps they frequently take and whether they’re always going to the pages/screens you expect them to;

See what actions and sequences of actions they perform once landed on the site/app or started a conversion funnel. Are these the actions you expect them to take?

Find out if there are stages where visitors experience troubles preventing them from completing your business goals. Do they go back at some point and go through a step once again?

Look into what users do after an app exception or seeing an error page on a site;

Analyze how a specific event impacts further users’ actions and whether this may discover some UX optimization insights.

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